AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on Twitter, Facebook, Instagram, YouTube and LinkedIn.
Machine Learning Scientist II - Cheminformatics
Here is an opportunity to work with the best of the best at the intersection of machine learning, deep learning, chemistry, and drug discovery to make a remarkable pan-Abbvie impact by enabling people to lead longer and healthier lives. As a Machine Learning Scientist, you will work as part of AbbVie’s Information Research RAIDERS: Pharma Discovery and Developmental Sciences team in conjunction with our partners across early as well as late drug Discovery.
You will bring together the power of science and technology at the interface of imaging, machine learning and data engineering to generate new understanding of the drug discovery process that contributes to finding better drugs faster. In this role, you will work as part of a highly capable and cross functional R&D team helping to bridge scientists from the domains of medicinal chemistry, computational chemistry and drug discovery by applying your expertise in ML and deep learning such as GNN, Geometric deep learning, Diffusion models, and LLM to extract insights from diverse data. You will apply your established technical skills and experience to deliver enterprise scale solutions capable of providing true insights that push forward the fundamental understanding of drug discovery. You will bring your solution architecture expertise to help design, develop, and deliver models and tools that extract and generate these insights. Come join us to help discover the cutting edge of drug discovery and help save lives.
As part of AbbVie’s global Business Technology Solutions, we are shaping the digital transformation accelerating the future of medicine—and doing it together, asking bold questions and taking on tough challenges through deep and honest collaboration. For anyone who wants to use technology and data to make a difference in people’s lives, contribute to the digital transformation of a leading biopharmaceutical company, and secure sustainable career growth within a diverse, global team: we’re ready for you.
In this role you’ll be responsible for:
- Define and support data transformation and preparation activities independently and in conjunction with data scientists.
- Hands on, design and deploy models and solutions built around deep and machine learning technologies in conjunction with medicinal Chemists and deep learning engineers/scientists.
- Hands on, design and deploy models and solutions built around molecule and chemistry assay data in conjunction with AbbVie domain scientists and experts.
- Advise on, design, and develop server-side programming components to support the delivery of solutions built on deep and machine learning models in conjunction with scientists affiliated with discovery and developmental sciences.
- Research, evaluate, and recommend process improvements, including automated systems and enhanced models in support of activities.
- Participate in a broader federated team of AI and automation specialists across AbbVie as part of the Information Research RAIDERS team, sharing expertise and educating a broader audience about solutions in your specialty.
Tools and skill you will use in this role:
- Ability to work in an agile, fast-paced research environment.
- Passion for exploratory projects, including proof-of-concept and proof-of-value engagements, and an ability to guide those concepts into production solutions.
- Ability to handle multiple projects at once.
- Collaborate with cross-functional teams to identify and address business problems using data-driven insights
- Work with large datasets to extract meaningful information and develop predictive models.
- Ability to communicate effectively with multiple groups within the organization and effectively collaborate with external partners.
Experiences that make you a strong candidate for this role:
- Bachelor’s degree with 5 years of relative work experience or Master’s degree and above with 4 years of relative work experience
- Expertise with developing, implementing and deploying programs and computational solutions employing Machine Learning/Deep learning (GNN, Geometric deep learning, Diffusion models, LLM etc.) and cheminformatic techniques.
- Familiarity with the basics of computer systems, Linux servers, and bash scripting.
- Proficiency in Python, AWS/cloud computing capabilities and tools.
- Experience with at least one or more ML frameworks such Pytorch, PyG, Tensorflow, Keras, and JAX.
- Experience with solution architecture development and deployment.
- Experience building and maintaining software systems in collaboration with others using version control tools (ideally GitHub)
- You have experience with drug discovery, chemistry, or AI for Science related projects (Ex: chemistry, chemical eng, cheminformatics etc.) and cheminformatics toolboxes such as RDKit, OpenEye, and OpenMM.
- You have software engineering experience or have built large software systems.
AbbVie is committed to operating with integrity, driving innovation, transforming lives, serving our community, and embracing diversity and inclusion. It is AbbVie’s policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information, gender identity or expression, sexual orientation, marital status, status as a protected veteran, or any other legally protected group status.
Significant Work Activities: Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)
Travel: Yes, 5 % of the Time
Job Type: Experienced
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